Developmental neurotoxicity (DNT) and many forms of reproductive toxicity (RT) often manifest themselves in functional deficits that are not necessarily based on cell death, but rather on minor changes relating to cell differentiation or communication. The fields of DNT/RT would greatly benefit from in vitro tests that allow the identification of toxicant-induced changes of the cellular proteostasis, or of its underlying transcriptome network. Therefore, the ‘human embryonic stem cell (hESC)-derived novel alternative test systems (ESNATS)’ European commission research project established RT tests based on defined differentiation protocols of hESC and their progeny. Valproic acid (VPA) and methylmercury (MeHg) were used as positive control compounds to address the following fundamental questions: (1) Does transcriptome analysis allow discrimination of the two compounds? (2) How does analysis of enriched transcription factor binding sites (TFBS) and of individual probe sets (PS) distinguish between test systems? (3) Can batch effects be controlled? (4) How many DNA microarrays are needed? (5) Is the highest non-cytotoxic concentration optimal and relevant for the study of transcriptome changes? VPA triggered vast transcriptional changes, whereas MeHg altered fewer transcripts. To attenuate batch effects, analysis has been focused on the 500 PS with highest variability. The test systems differed significantly in their responses (<20 % overlap). Moreover, within one test system, little overlap between the PS changed by the two compounds has been observed. However, using TFBS enrichment, a relatively large ‘common response’ to VPA and MeHg could be distinguished from ‘compound-specific’ responses. In conclusion, the ESNATS assay battery allows classification of human DNT/RT toxicants on the basis of their transcriptome profiles.Electronic supplementary materialThe online version of this article (doi:10.1007/s00204-012-0967-3) contains supplementary material, which is available to authorized users.

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Abstract. One of the major challenges in the development of central nervous system (CNS)-targeted drugs is predicting CNS exposure in human from preclinical data. In this study, we present a methodology to investigate brain disposition in rats using a physiologically based modeling approach aiming at improving the prediction of human brain exposure. We specifically focused on quantifying regional diffusion and fluid flow processes within the brain. Acetaminophen was used as a test compound as it is not subjected to active transport processes. Microdialysis probes were implanted in striatum, for sampling brain extracellular fluid (ECF) concentrations, and in lateral ventricle (LV) and cisterna magna (CM), for sampling cerebrospinal fluid (CSF) concentrations. Serial blood samples were taken in parallel. These data, in addition to physiological parameters from literature, were used to develop a physiologically based model to describe the regional brain pharmacokinetics of acetaminophen. The concentration-time profiles of brain ECF, CSF LV , and CSF CM indicate a rapid equilibrium with plasma. However, brain ECF concentrations are on average fourfold higher than CSF concentrations, with average brain-to-plasma AUC 0−240 ratios of 121%, 28%, and 35% for brain ECF, CSF LV , and CSF CM , respectively. It is concluded that for acetaminophen, a model compound for passive transport into, within, and out of the brain, differences exist between the brain ECF and the CSF pharmacokinetics. The physiologically based pharmacokinetic modeling approach is important, as it allowed the prediction of human brain ECF exposure on the basis of human CSF concentrations.

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